Citation

Kim K, Yamashita EY. J. Adv. Transp. 2007; 41(1): 69-89.

Affiliation

University of Hawaii, Hawaii, United States.

Copyright

(Copyright © 2007, Institute for Transportation, Publisher John Wiley and Sons)

DOI

unavailable

PMID

unavailable

Abstract

The purpose of this paper is twofold: 1) to describe a statistical technique known as K-means clustering in term of its advantages and disadvantages in safety research; and, 2) to use this method to analyze spatial patterns of pedestrian-involved crashes in Honolulu. K-means, a partitioning clustering technique, provides a powerful tool for analyzing and visualizing spatial patterns. While there are other techniques, one of the advantages of the K-means approach is that it is a well established technique that has been used for many different applications other than traffic safety. In this paper, we compare it to hierarchical clustering techniques and suggest that both are useful in the arsenal of spatial analytic tools for safety research.